US11559616B2 - Method and system for postdialytic determination of dry weight - Google Patents
Method and system for postdialytic determination of dry weight Download PDFInfo
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- US11559616B2 US11559616B2 US15/679,656 US201715679656A US11559616B2 US 11559616 B2 US11559616 B2 US 11559616B2 US 201715679656 A US201715679656 A US 201715679656A US 11559616 B2 US11559616 B2 US 11559616B2
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
- A61M1/14—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
- A61M1/14—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis
- A61M1/16—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis with membranes
- A61M1/1601—Control or regulation
- A61M1/1603—Regulation parameters
- A61M1/1611—Weight of the patient
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4869—Determining body composition
- A61B5/4875—Hydration status, fluid retention of the body
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- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
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- A—HUMAN NECESSITIES
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- A61B6/00—Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
- A61M1/14—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis
- A61M1/16—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis with membranes
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
- A61M1/14—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis
- A61M1/16—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis with membranes
- A61M1/1601—Control or regulation
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- A—HUMAN NECESSITIES
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- A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
- A61M1/14—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis
- A61M1/16—Dialysis systems; Artificial kidneys; Blood oxygenators ; Reciprocating systems for treatment of body fluids, e.g. single needle systems for hemofiltration or pheresis with membranes
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- A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
- A61M1/34—Filtering material out of the blood by passing it through a membrane, i.e. hemofiltration or diafiltration
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- A61M1/00—Suction or pumping devices for medical purposes; Devices for carrying-off, for treatment of, or for carrying-over, body-liquids; Drainage systems
- A61M1/34—Filtering material out of the blood by passing it through a membrane, i.e. hemofiltration or diafiltration
- A61M1/3413—Diafiltration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
- G16H20/17—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
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- A—HUMAN NECESSITIES
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- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M2205/00—General characteristics of the apparatus
- A61M2205/33—Controlling, regulating or measuring
- A61M2205/3327—Measuring
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M2205/00—General characteristics of the apparatus
- A61M2205/50—General characteristics of the apparatus with microprocessors or computers
- A61M2205/52—General characteristics of the apparatus with microprocessors or computers with memories providing a history of measured variating parameters of apparatus or patient
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M2230/00—Measuring parameters of the user
- A61M2230/20—Blood composition characteristics
- A61M2230/207—Blood composition characteristics hematocrit
Definitions
- the present invention relates to a method and a system (and, respectively, an apparatus) for a measuring system for determining the dry weight of a patient in the dialysis routine. Especially, the invention relates to evaluating the dry weight obtained during dialysis therapy.
- the determination of dry weight in dialysis routine is usually based on experiences and routines of the hospital staff, wherein e.g. the courses of blood pressure and blood volume of the therapies are evaluated and, accordingly, adequate dry weight is determined.
- vena-cava diameter measurement the diameter of the lower vena cava is determined with ultrasound. Due to the fluid retention in the interdialytic period of time, the veins are more expanded than in normally hydrogenated persons. The determined diameter of the vein is then compared to particular reference values. E.g. a diameter of 11 mm/m 2 indicates hypervolemia, whereas a diameter of 8 mm/m 2 indicates hypovolemia.
- the hematocrit content (Hct content corresponding to the share of erythrocytes in the blood) of the blood is determined by which the water content in the blood can be traced back.
- a high Hct content/value related to a defined volume indicates a low fluid level.
- a low Hct value indicates hypervolemia.
- the blood volume is continuously read out during a therapy by a Hct sensor, and by way of the curve forming in this way a statement can be made about the water balance of the patient.
- the course of the blood volume curve is largely dependent on the ratio of the ultrafiltration rate to the endogenous refilling. If high refilling and, accordingly, a flat blood volume curve are provided, a possible hypervolemia can be concluded.
- a marker for the atrial natriuretic peptide can be utilized.
- ANP is formed and released in the cell tissue.
- ANP plays a decisive role for the water-salt homeostasis and has a very low dialysis clearance (the renal clearance indicates the elimination (“clearing”) of a substance from the blood plasm).
- said marker offers a good possibility of determining the endogenous fluid balance before and after dialysis. It was found that the ANP concentration definitely varies during a dialysis therapy and shows good correlations with the blood pressure.
- the afore-mentioned approaches have not or only partly become accepted in the dialysis routine, as they provide only clues for an assessment of the dry weight.
- the dry weight is usually continued to be determined with the empirical values of the dialysis staff only.
- the vein diameter is determined only at particular points in time (e.g. before, during or after the therapy). Influencing factors such vasoconstriction or other diseases which have an impact on the diameter of the vein are not taken into account. Further, changes of the vein diameter among different patients may have strong variations. This method further requires an additional ultrasonic apparatus and an interpreting physician, which entails an increased employment and cost of staff.
- Blood volume monitoring is no direct method of determining the dry weight. This method provides the physician only with a clue which is considered by the physician for his/her personal estimation. Although the system provides precise values about the water content which is currently and related to the start of therapy provided in the blood, no statement is made, however, either about possible hypervolemia or hypovolemia or about the water quantity in the other reservoirs.
- the physician in charge has to evaluate the blood volume values on his/her own and, based on his/her experience, has to decide whether the dry weight will be maintained or shall be modified in further therapies. Hence, this is sort of a trial-and-error method in which the physician considers the behavior of the blood volume and then takes decisions regarding the amount of ultrafiltration. For this reason, this method provides no exact information about a dry weight which is chosen to be too high or too low.
- the method using the biochemical markers allows detecting hypervolemia after therapy.
- hypovolemia cannot be determined by this method.
- the result of hypervolemia depends on the cardiac function of the patient, as said function decisively influences the filling level and thus also the transmural pressure.
- the results of this method are insecure measured by the current standards. It is another drawback that this method is very complicated and time-consuming for mass application, as laboratory analyses and additional equipment as well as staff members for operating said additional equipment are required.
- An object underlying the present invention is, inter alia, to provide a system, an apparatus, and a method of determining dry weight of a patient with which automatic and automated evaluation/judgment of the dry weight and easy implementation in existing systems are possible.
- the rate of change or increase of the so-called blood volume rebound is determined upon reaching a set/predetermined ultrafiltration volume and it is checked with the aid of the learning means (e.g. neuronal network) whether a dry weight predefined for a patient has been reached and, unless this is the case, in how far the ultrafiltration volume can be adapted.
- the learning means e.g. neuronal network
- an automatic evaluation of the dry weight is following, in contrast to the conventional approaches for mathematic or measuring processes which still have to be assessed and interpreted by the staff members in charge.
- the suggested system/apparatus and method, respectively, for determining the dry weight thus can be easily implemented in already existing systems (if the conventional system includes blood volume monitoring) and trains itself in a fully automated manner by the learning means and, respectively, the learning step.
- system, the apparatus, and, respectively, the method can be adapted to individual patients and at the end of each therapy furnishes an explicit statement about reaching the dry weight as well as possible adaptations of the ultrafiltration volume.
- a learning means e.g. neuronal network
- the integrated learning means and, respectively, the integrated learning step allow for independent learning and independent optimizing of the dry weight determination.
- the latter can be fully automated and no additional measuring instruments are required, which thus does not entail any special expenditure for the patient and the staff members.
- FIG. 1 shows a flow diagram of a method for determining the dry weight according to a first embodiment
- FIG. 2 shows a schematic architecture of a neuronal network for use in the present invention
- FIG. 3 shows a table including exemplary results of various cycles of a neuronal network
- FIG. 4 shows another table including exemplary results of various cycles of different neuronal networks having different input levels and hidden levels.
- the blood volume rebound i.e. the increase in the blood volume after termination of the therapy, is used to make a statement about reaching the dry weight and the degree of a possible hypervolemia or hypovolemia.
- the higher the increase in the blood volume in the wake of therapy the higher the degree of hypervolemia of the patient and the higher the still tolerable ultrafiltration volume/the still tolerable ultrafiltration quantity.
- the increase in the blood volume upon termination of the therapy can be automatically evaluated and an exact statement about reaching the dry weight can be made.
- the blood volume values after reaching the given/predetermined ultrafiltration value are recorded for a certain period of time and are evaluated with the aid of a learning means (e.g. a neuronal network) based on an algorithm, for example.
- the learning means then calculates/establishes the still missing or the superfluous ultrafiltration volume so that the physician may appropriately adapt his/her next therapies.
- a neuronal network is provided as an example of the learning means which evaluates the increase in the rebound so as to determine the required ultrafiltration volume for reaching the dry weight.
- the neuronal network may be trained, for example, with the aid of data of clinical studies (carried out before) or other predetermined training data. The training thus constitutes a prerequisite for the definition of an established neuronal network for determining or judging the dry weight. For said data in the case of stable dialysis patients having a known dry weight the ultrafiltration is stopped at a particular point in time before the end of therapy at a known remaining ultrafiltration volume and the blood volume rebound is recorded for 15 minutes (e.g.
- the pairs of data obtained in this way are transmitted to the network for training.
- the neuronal network learns from the training which blood volume rebound corresponds to which volume quantity. Following the studies, the trained neuronal network is implemented in the dialysis machine.
- FIG. 1 illustrates a flow diagram of a (control) method for determining the dry weight according to a first embodiment.
- the method may be implemented e.g. as a computer program whose code mediums (instructions etc.) generate the following steps, when the program is run on a computer system.
- step 101 a dialysis therapy including blood volume monitoring is carried out.
- the therapy parameters e.g. time of therapy
- a predetermined period e.g. 15 min
- step 102 it is checked whether or not the time of therapy minus the predetermined period has been reached already. When the therapy time minus the predetermined period is reached, the cycle proceeds along the yes branch (J) to step 103 . Otherwise, the cycle returns to step 101 along the no branch (N).
- step 103 it is checked whether or not the desired ultrafiltration volume is reached. Unless the ultrafiltration volume is reached, the cycle proceeds along the no branch (N) to step 104 and the therapy is continued until the ultrafiltration volume is reached or is terminated and the excessive volume will be withdrawn during the next therapy.
- step 103 If it is determined in step 103 , on the other hand, that the ultrafiltration volume has been reached, the cycle proceeds along the yes branch (J) to step 105 and the therapy is carried out without any ultrafiltration up to the end of the therapy time. During the residual time of the predetermined period (e.g. 15 min) the blood volume monitoring is continued.
- the predetermined period e.g. 15 min
- step 106 it is checked whether the therapy time has been reached. If this is not the case, the cycle returns to step 105 along the no branch (N). Otherwise, the cycle proceeds along the yes branch (J) to step 107 where the blood volume values, more exactly speaking the blood volume rebound, are stored for evaluating the dry weight and are evaluated by the neuronal network. After this evaluation, the neuronal network checks in the subsequent step 108 whether the dry weight has been reached. If in step 108 it is determined, based on the empirical values of the neuronal network learnt by training, that the dry weight has not yet been reached, the cycle proceeds along the no branch (N) to step 109 where it is checked whether hypervolemia or hypovolemia of the patient is given.
- step 109 hypervolemia is calculated, the cycle proceeds along the yes branch (J) to step 110 where the patient is automatically continued being ultrafiltrated or a physician (system user) is informed about the hypervolemia.
- step 109 hypovolemia is calculated
- the cycle proceeds along the no branch (N) to step 111 where e.g. automatically an infusion of a physiologic salt solution is triggered as a bolus or the physician (system user) is informed about the hypovolemia.
- step 108 If it is determined in step 108 that the dry weight has been reached, the cycle proceeds along the yes branch (J) to step 112 and the process is terminated. The therapy thus can be terminated.
- a neuronal network that is individual for each patient which can be individually adapted to the patient.
- data pairs of rebound ultrafiltration quantity can be established for the respective patient and can be transmitted to the neuronal network for training. This is only possible, however, when the patient has reached a stable condition already and therefore the dry weight is largely known, as otherwise no statement can be made about the remaining ultrafiltration volume. If this is the case, as in the afore-described studies the ultrafiltration can be stopped from a particular point in time and the blood volume rebound can be recorded until the end of therapy.
- the pairs of data of the individual patient obtained in this way are input to the system for training so that the neuronal network is continuously capable of furnishing precise statements about the fluid balance of the respective patient.
- Another variant for the neuronal network that is individual for each patient is a continuous training for which input information is required from the medical staff.
- the staff members adjust an ultrafiltration volume and wait for the blood volume rebound at the end of therapy.
- the blood volume rebound is evaluated with the aid of said neuronal network and the operator is requested to judge whether the displayed statement is correct. Unless this is the case, the operator is requested to inform the system about the hydration condition of the patient and about his/her possible adaptations to the ultrafiltration volume.
- Said data are stored again and are made available to another neuronal network, the personal neuronal network, for training. In this way, the personal neuronal network is automatically adjusted to the respective patient over time and with the aid of the operator.
- the network can be newly adapted and trained at any time.
- a neuronal network was chosen which evaluates blood volume values and, on the basis thereof, calculates the dry weight.
- FIG. 2 illustrates a schematic architecture of a neuronal network for use in the embodiments.
- a neuronal network may be implemented as a software solution which is applied for identifying patterns and courses, for fitting curves and for further problems. It consists of an input layer 201 which may contain any number of input parameters 20 . This layer is followed by one or more hidden layers 202 which are linked to each other via different activating functions (e.g. sigmoid function). Each hidden layer 202 may have a variable number of neurons 23 . Finally, the last hidden layer 202 leads to the output layer 203 which outputs one or more output parameters 24 . It is important to mention that, depending on the selected number of hidden layers 202 and neurons 23 , the expected results and the capability of the network may strongly vary (which can be determined with the aid of the mean square error (MSE) between the calculated output and the actual output). With a large number of layers and neurons, respectively, overfitting may easily occur, whereas a low number does not offer sufficient space for exactly weighting the output.
- MSE mean square error
- Each neuronal network passes two steps: training and validation.
- training there are different training algorithms such as e.g. the back-propagation process, which shall not be discussed in detail here, however.
- known input-output pairs are transmitted to the network.
- the network attempts to achieve the expected output via the different activating functions to which the neurons are linked. Accordingly, the neuronal network weights the different connections 22 between the neurons 23 of the different layers in a differently strong way, until a certain error tolerance or a maximum number of training cycles has been reached.
- Validation is performed after the training in that again known input-output pairs are transmitted to the network and the latter compares the correct outputs to the ones calculated by itself.
- a neuronal network was drafted, trained and validated with the help of 48 therapy data.
- Said therapy data comprised blood volume, ultrafiltration and blood pressure values of anonymous dialysis patients.
- the neuronal network requires blood volume rebound values that are missing in the therapy data. For this reason, the blood volume rebound was processed from the individual therapy data as follows.
- the training was carried out with 30 out of 48 of the afore-mentioned therapy data.
- the best possible network parameters were determined for evaluation of the processed blood volume rebounds.
- the input parameters were transmitted to different network configurations, were trained and validated.
- three different respective input parameters blood volume rebound, blood volume rebound plus the last blood volume value of the therapy, blood volume values of the complete therapy
- Each configuration was trained ten times.
- the neuronal network with the best performance out of 11970 individual trainings, for example, was obtained.
- FIG. 3 illustrates a table including exemplary results of the best outputs of different cycles of a neuronal network.
- FIG. 4 shows another table including exemplary results of different cycles of various neuronal networks having different input levels and hidden levels.
- the representation of the results of the second neuronal network 2 and of the third neuronal network 3 serve for illustration of the fact that a neuronal network with a certain number of hidden layers and input parameters need not always show good performance.
- patients' data are necessary. These data can be collected from different dialysis centers and can be processed within the scope of a clinical study (carried out before). Within the scope of said study, stable patients having a known dry weight are involved. With said patients the therapy is stopped, before the end of therapy, at a known residual amount of ultrafiltration volume and the blood volume rebound is recorded over a particular period of time. If possible, also data are detected in which the ultrafiltration volume is even increased in a defined manner.
Abstract
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CN110152087A (en) * | 2019-04-19 | 2019-08-23 | 暨南大学 | A kind of monitoring method of blood dialysis |
JP2022153793A (en) * | 2021-03-30 | 2022-10-13 | 株式会社ジェイ・エム・エス | Setting proposal device, dialyzer, learning device and dialysis information system |
Citations (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2002165876A (en) | 2000-12-01 | 2002-06-11 | Nipro Corp | Hemocatharsis apparatus |
US20030120170A1 (en) | 2000-08-14 | 2003-06-26 | Fansan Zhu | Device and method for monitoring and controlling physiologic parameters of a dialysis patient using segmental bioimpedance |
US20050197982A1 (en) * | 2004-02-27 | 2005-09-08 | Olivier Saidi | Methods and systems for predicting occurrence of an event |
US20070108129A1 (en) * | 2005-11-11 | 2007-05-17 | Nikkiso Co., Ltd. | Hemodialysis apparatus and method for hemodialysis |
CN101193667A (en) | 2005-04-08 | 2008-06-04 | 日机装株式会社 | Hemodialysis apparatus and method for hemodialysis |
CN102159260A (en) | 2008-09-15 | 2011-08-17 | B·布莱恩·阿维图姆股份公司 | Method and device to early predict kt/v parameter in kidney substitution treatments |
WO2013043598A1 (en) | 2011-09-19 | 2013-03-28 | Fresenius Medical Care Holdings, Inc. | Estimation of the dry weight of a dialysis patient |
US20130331712A1 (en) * | 2010-12-23 | 2013-12-12 | Fresenius Medical Care Deutschland Gmbh | Method for calculating or approximating a value representing the relative blood volume and devices |
US20140200181A1 (en) * | 2011-09-08 | 2014-07-17 | Doris Helene Fuertinger | System and method of modeling erythropoiesis and its management |
US20140316292A1 (en) * | 2013-04-19 | 2014-10-23 | Semler Scientific, Inc. | Circulation Monitoring System |
US20150045713A1 (en) | 2013-08-07 | 2015-02-12 | B. Braun Avitum Ag | Device and method for predicting intradialytic parameters |
US20160058933A1 (en) * | 2007-02-27 | 2016-03-03 | Deka Products Limited Partnership | Control Systems and Methods for Blood or Fluid Handling Medical Devices |
US20180050144A1 (en) | 2016-08-22 | 2018-02-22 | B. Braun Avitum Ag | Method and system for postdialytic determination of dry weight |
-
2016
- 2016-08-22 DE DE102016115496.2A patent/DE102016115496A1/en active Pending
-
2017
- 2017-08-16 EP EP17186368.1A patent/EP3287156B1/en active Active
- 2017-08-17 US US15/679,656 patent/US11559616B2/en active Active
- 2017-08-17 JP JP2017157633A patent/JP7071805B2/en active Active
- 2017-08-22 CN CN201710724814.3A patent/CN107754034B/en active Active
- 2017-08-22 CN CN201721053072.8U patent/CN209529783U/en active Active
-
2022
- 2022-12-14 US US18/081,542 patent/US20230122618A1/en active Pending
Patent Citations (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030120170A1 (en) | 2000-08-14 | 2003-06-26 | Fansan Zhu | Device and method for monitoring and controlling physiologic parameters of a dialysis patient using segmental bioimpedance |
JP2002165876A (en) | 2000-12-01 | 2002-06-11 | Nipro Corp | Hemocatharsis apparatus |
US20050197982A1 (en) * | 2004-02-27 | 2005-09-08 | Olivier Saidi | Methods and systems for predicting occurrence of an event |
CN101193667A (en) | 2005-04-08 | 2008-06-04 | 日机装株式会社 | Hemodialysis apparatus and method for hemodialysis |
US20110089111A1 (en) | 2005-04-08 | 2011-04-21 | Nikkiso Co., Ltd. | Hemodialysis apparatus and method for hemodialysis |
US8496807B2 (en) | 2005-11-11 | 2013-07-30 | Nikkiso Co., Ltd. | Hemodialysis apparatus and method for hemodialysis |
US20070108129A1 (en) * | 2005-11-11 | 2007-05-17 | Nikkiso Co., Ltd. | Hemodialysis apparatus and method for hemodialysis |
CN101304773A (en) | 2005-11-11 | 2008-11-12 | 日机装株式会社 | Hemodialysis apparatus and method for hemodialysis |
US20160058933A1 (en) * | 2007-02-27 | 2016-03-03 | Deka Products Limited Partnership | Control Systems and Methods for Blood or Fluid Handling Medical Devices |
US8568595B2 (en) | 2008-09-15 | 2013-10-29 | B. Braun Avitum Ag | Method and device to early predict the Kt/V parameter in kidney substitution treatments |
CN102159260A (en) | 2008-09-15 | 2011-08-17 | B·布莱恩·阿维图姆股份公司 | Method and device to early predict kt/v parameter in kidney substitution treatments |
US20130331712A1 (en) * | 2010-12-23 | 2013-12-12 | Fresenius Medical Care Deutschland Gmbh | Method for calculating or approximating a value representing the relative blood volume and devices |
US20140200181A1 (en) * | 2011-09-08 | 2014-07-17 | Doris Helene Fuertinger | System and method of modeling erythropoiesis and its management |
WO2013043598A1 (en) | 2011-09-19 | 2013-03-28 | Fresenius Medical Care Holdings, Inc. | Estimation of the dry weight of a dialysis patient |
US20140249384A1 (en) | 2011-09-19 | 2014-09-04 | Fresenius Medical Care Deutschland, Gmbh | Estimation of the dry weight of a dialysis patient |
JP2014530669A (en) | 2011-09-19 | 2014-11-20 | フレゼニウスメディカル ケア ホールディングス インコーポレイテッド | Estimating dry weight of dialysis patients |
US20140316292A1 (en) * | 2013-04-19 | 2014-10-23 | Semler Scientific, Inc. | Circulation Monitoring System |
US20150045713A1 (en) | 2013-08-07 | 2015-02-12 | B. Braun Avitum Ag | Device and method for predicting intradialytic parameters |
DE102013108543A1 (en) | 2013-08-07 | 2015-02-26 | B. Braun Avitum Ag | Apparatus and method for predicting intradialytic parameters |
US20180050144A1 (en) | 2016-08-22 | 2018-02-22 | B. Braun Avitum Ag | Method and system for postdialytic determination of dry weight |
CN209529783U (en) | 2016-08-22 | 2019-10-25 | B·布莱恩·阿维图姆股份公司 | System for being determined after the dialysis of dry weight |
Non-Patent Citations (9)
Title |
---|
Chinese Examination Report received in Application No. 201710724814.3 dated Dec. 25, 2020, 31 pages. |
Chinese Search Report received in Application No. 201710724814.3 dated Dec. 17, 2020, 6 pages. |
European search report for European Application No. 17186368.1, dated Jan. 17, 2018 with translation, 14 pages. |
German Search Report for German Application No. 10 2016 115 496.2, with partial translation, dated Apr. 3, 2017—17 Pages. |
Lopot et al., "Continuous Blood Volume Monitoring and ‘Dry Weight’ Assessment", Journal of Renal Care, Apr. Jun. 2007, pp. 52-58. |
Office Action received in Chinese Application No. 201710724814.3 dated Aug. 20, 2021, with translation, 12 pages. |
Office Action received in Japanese Application No. 2017-157633 dated Aug. 3, 2021, with translation, 5 pages. |
Rodriguez et al., "Assessment of dry weight by monitoring changes in blood volume during hemodialysis using Crit-Line", Kidney International, vol. 68 (2005), pp. 854-861. |
Search Report received in Chinese Application No. 201710724814.3 dated Aug. 11, 2021, with translation, 4 pages. |
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DE102016115496A1 (en) | 2018-02-22 |
JP7071805B2 (en) | 2022-05-19 |
CN209529783U (en) | 2019-10-25 |
US20180050144A1 (en) | 2018-02-22 |
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